Utilizing recent findings on rotation equivariant CNNs, Veeling et al. [1]} proposed a model that leverages rotational symmetries in a principled manner. They presented a visual analysis showing improved stability on predictions, and demonstrate that exploiting rotation equivariance significantly improves tumor detection performance on a challenging lymph node metastases dataset.
